Separating the Wheat from the Chaff: Using Indexing and Sub-Sequence Mining Techniques to Identify Related Crashes During Bug Triage

2022 IEEE 22nd International Conference on Software Quality, Reliability and Security (QRS) Pub Date : 2022-12-01 DOI:10.1109/QRS57517.2022.00014

Kedrian James, Yufei Du, Sanjeev Das, F. Monrose

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引用次数: 1

Abstract

Bug triaging entails a laborious process wherein triagers spend time examining new bug reports, localizing the bugs, and assigning them to the appropriate developer(s) to fix the bugs. In recent years, the adoption of automated software testing techniques (e.g., fuzzing) further complicates the process because bug hunters can submit an overwhelming number of reports in a short period. To lessen these pain points, we present an approach that extracts a fingerprint from crash information within a bug report, and returns a group of bugs with similar behaviors. Our approach uses symptoms of the crash to create a robust fingerprint, and leverages MinHashing and Locality Sensitive Hashing to match crashes, as well as a sequential pattern mining algorithm to find frequent closed sequences among bugs. Our evaluation shows that our approach outperforms contemporary approaches (e.g., finding previously unknown duplicates among 81 CVEs), and saves triagers time and effort.

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从谷壳中分离小麦:使用索引和子序列挖掘技术来识别Bug分类过程中的相关崩溃

Bug分类需要一个费力的过程，在这个过程中，分类者花时间检查新的Bug报告，定位Bug，并将它们分配给适当的开发人员来修复Bug。近年来，自动化软件测试技术(例如，模糊测试)的采用使这个过程进一步复杂化，因为bug猎人可以在短时间内提交大量的报告。为了减少这些痛点，我们提出了一种方法，从bug报告中的崩溃信息中提取指纹，并返回一组具有相似行为的bug。我们的方法使用崩溃的症状来创建一个健壮的指纹，并利用MinHashing和Locality Sensitive Hashing来匹配崩溃，以及一个顺序模式挖掘算法来查找bug之间频繁的封闭序列。我们的评估表明，我们的方法优于当代的方法(例如，在81个cve中发现以前未知的重复)，并节省了triagers的时间和精力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2022 IEEE 22nd International Conference on Software Quality, Reliability and Security (QRS)

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